Process Development Engineer: Biotech Batch-Scale Optimizer

ArrowBiome Pte. Ltd.; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

ArrowBiome Pte. Ltd. in Singapore seeks a Process Development Engineer to support in-house manufacturing and development of biologically active ingredient processes and particle-based formulations.

You will run bench-scale operations, document batches, and contribute to scale-up and transfer readiness, with a focus on reliability and reproducibility. Candidates should hold a relevant science degree and have up to 5 years of lab experience, with strong emphasis on experimental discipline and data

Qualifications

• Bachelor-level degree in chemistry, polymers, materials science, chemical engineering, pharma or biology.
• Up to 5 years' relevant lab experience is desirable.
• Internship or final-year project work is considered.

Responsibilities

• Run bench-scale formulation and particle-processing activities per procedures.
• Deliver batches safely and reproducibly, including multi-day experiments.
• Characterise samples and perform in-process testing (moisture, particle size, microscopy).
• Maintain lab equipment, calibration, consumables and safety practices.
• Troubleshoot routine issues and raise deviations when needed.
• Maintain accurate batch records and support change-control activity.

Skills

Lab formulation

Batch execution

Characterisation

Lab safety

Troubleshooting

Education

Bachelor's degree in Chemistry/Polymer/Materials Science or related

Tools

Electronic lab notebooks

Job description

ArrowBiome Pte. Ltd. in Singapore seeks a Process Development Engineer to support in-house manufacturing and development of biologically active ingredient processes and particle-based formulations.

You will run bench-scale operations, document batches, and contribute to scale-up and transfer readiness, with a focus on reliability and reproducibility. Candidates should hold a relevant science degree and have up to 5 years of lab experience, with strong emphasis on experimental discipline and data